System and method of predicting efficacy of tongue-base therapies

ABSTRACT

A method, computer-readable medium, and system for predicting a response to tongue-base therapies (particularly as it relates to obstructive sleep apnea) are provided. The method includes generating with a processing element a plurality of images of at least a portion of a patient&#39;s anatomy, acquiring data indicative of the portion of the patient&#39;s anatomy from the images, and determining a probability of a patient&#39;s response to a tongue-base treatment based on the acquired data.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention is related to the field of tongue-base therapies(particularly as relates to obstructive sleep apnea), and moreparticularly, to a system and method of predicting the efficacy oftongue-base therapies (particularly for the treatment of obstructivesleep apnea).

2. Description of Related Art

Obstructive sleep apnea (OSA) has been found to be as common asdiabetes, asthma, and hypertension. Like those multi-systemic problems,OSA affects a large percentage of the population. However, with properdiagnosis and treatment, patients can live a normal life, andlife-threatening risks are reduced.

The prevalence of OSA has been estimated to be 20% in the World's adult(25+ years of age) population (or approximately 660 million), withapproximately 7% of all adults (˜230 million) suffering from moderate tosevere forms of the condition. The estimated incidence of mild OSA iseven larger (estimated ˜400 million). In the USA alone, an estimated 1in 5 (˜40 million) adults suffer from some form of OSA, with 1 in 15(˜15 million) adults having moderate to severe forms of OSA. Theawareness and diagnosis of OSA are growing. Analysts estimate that fewerthan 4% of OSA sufferers are currently diagnosed and being treated. This“undiagnosed patient gap” has created one of the fastest growingsegments of the medical device industry, and this percentage is forecastby analysts to increase to over 24% by 2012.

Driving market growth coupled with an aging population (OSA riskincreases over 40 years of age) have increased awareness of the publicand the media and diagnosis by physicians. OSA is considered a riskfactor for stroke and congestive heart failure, indications that arecurrently being studied in multicenter clinical trials.

There is no known cure for obstructive sleep apnea. Behavioraltreatments such as weight loss and alcohol avoidance may be helpful, butare not always completely effective therapies. Surgical procedures areconsidered second line therapies and current surgical modalities resultin inconsistent results. While airway pressure treatment is consideredto be the first line of therapy worldwide (and has proven to be the mostsuccessful therapy in maintaining an open airway), this form oftreatment suffers from a significant incidence of side-effects, andthere is an equally significant lack of long-term patient compliance.The competitive environment for OSA therapeutic devices can be segmentedinto three main categories based upon treatment methods: nasal maskcontinuous positive airway pressure (CPAP), passive mandibularadvancement oral appliances (OAT), and active oral positive airwaypressure devices.

For nearly all patients diagnosed with some form of OSA, the mostprescribed treatment (80% of all Rx's) is a nasal mask plus air flowgenerator machine for the delivery of nasal CPAP, variable pressureBi-level, or Auto-titration (“smart”) CPAP systems to “splint open” theairway allowing air to flow freely to the lungs during periods of airwayocclusion. CPAP systems have been found effective in treating mild,moderate, and severe cases of OSA and are considered the gold standardtreatment modality.

Problematic to this form of treatment, however, is non-compliance. TheAmerican Sleep Disorders association estimated in 1993 thatapproximately 50% of patients prescribed CPAP systems were non-compliant(i.e., use of CPAP less than 4 hours per night). Non-compliance is theextreme manifestation of patient dissatisfaction with nasal CPAP; evencompliant patients are not satisfied, as evidenced by the wide range ofproblems encountered by all users of nasal CPAP mask systems (e.g.,nasal stuffiness, mask leak, dry throat, cold air stream, mask rubbing,more frequent awakenings, red/sore eyes, and nosebleeds).

Major factors in non-compliance are bulkiness, discomfort, and leakageproblems inherent in the nasal mask CPAP systems. The number onecomplaint by OSA patients is the discomfort caused by their nasal mask.Poor training and follow-up from the device distributor, claustrophobia,nasal congestion, discomfort, complications with headgear adjustments,and nasal and skin allergies are also problematic. Excessive sinusirritation, injury, or physical deformities make nasal CPAP impractical.CPAP use is also associated with a limitation on the part of the patientto sleep in varying body positions while connected to the device; CPAPusers are required to sleep only on their back or sides (they are unableto sleep in the prone position, i.e., on their stomachs). Patienthealth, public safety, and economic productivity all suffer when OSApatients fail to comply. All of these factors combined often promoteseeking of alternative forms of treatment for this disorder, asdescribed below.

Passive Dental Mandibular Advancement Appliances (OAT) affectadvancement of the lower jaw, and are used to reposition the tongue inthe oropharyngeal cavity to create a larger air passageway. Thesedevices are useful as a primary treatment in a large percentage of casesof snoring and mild-moderate OSA (and in some isolated cases of severeOSA) and are often useful in cases of persistent apnea following failedsoft palate or other upper airway surgery. Sleep physicians, generaldentists, oral & maxillofacial surgeons, other dental specialists, andotolaryngologists often prescribe this treatment.

Based upon recent studies, a newly published Practice Parameter Paperproduced by the American Academy of Sleep Medicine has added substantialcredibility to this form of treatment, as numerous recent Level I and IIstudies have significantly elevated the level of knowledge surroundinguse of these appliances and verified efficacy of this treatment. Inparticular, the American Academy of Sleep Medicine has revised itspreviously published practice parameters to now recommend first-line useof oral appliances in mild to moderate OSA (in those patients who preferoral appliances to CPAP, or who are intolerant to CPAP therapy).Importantly, Level I evidence exists which suggests that OAT therapy ismore effective than soft palate surgery in patients with mild-moderateOSA, and it is expected that prescriptions for this form of treatmentwill increase in the future.

Side-effects of OAT include potential changes in dental occlusion,Temporomandibular Joint symptom exacerbation, and current lack ofcapability to specifically predict who will respond best to thistreatment.

Active Oral Positive Airway Pressure Devices deliver positive pressureairflow via the oral cavity (bypassing the nasal airway). Oral PositiveAirway Pressure (OPAP) incorporates mandibular advancement and positivepressure ventilation, while other masks (such as the Oracle mask)deliver positive pressure ventilation alone without incorporatingmandibular advancement. Minimal long-term data are available with thistechnique, and airway drying (despite the use of humidified circuits) isproblematic.

Pharmacologic treatments for OSA have been ineffective. The fundamentalcause of OSA is anatomically related and not impacted biochemically.

Various surgical techniques have been developed to treat OSA.Uvulopalatopharyngoplasty (UPPP) treatment includes resection of theuvula and portions of the soft palate to widen the oropharyngeal space.Although snoring is temporarily relieved in most cases, apnea oftenpersists due to continued tongue-base narrowing. The overall successrate of UPPP is about 40% for primary snoring, but less for apnea(problematic is that many physicians fail to obtain objective sleepstudy data either before or following performance of this procedure, anda “silent apnea” situation is often created). Velopharyngealincompetence and pharyngeal stenosis are significant complications toall forms of soft palate surgery.

Laser-Assisted Uvulopalatopharyngoplasty (LAUP) performs a similarresult as the above utilizing a CO₂ laser. Laser treatment may worsenthe respiratory disturbance index (RDI) and can cause long-term sequelaeof a scarred airway. While snoring may be diminished, the diagnosis ofOSA may be delayed because the primary symptom of OSA, i.e., snoring, iseliminated.

Genioglossus advancement procedure (GBAT) procedure includes advancingthe genioglossus attachment to the mandibular symphysis forward andfixating the same with plates and/or screws. Importantly, the long-termresults of this technique are unknown, and clinical data surrounding theuse of this technique are limited as it is often performed at the sametime soft palate surgery is performed.

Maxillomandibular Advancement (MMA) has proven effective at reducingsnoring and OSA in patients that have failed other therapies and whohave clear anatomical abnormalities warranting a more intensiveintervention. This procedure involves surgical repositioning of theupper and lower jaws. While the surgical literature suggests that thisprocedure has the greatest impact on affecting volumetric expansion atmultiple areas of the upper airway (and is considered the mostsuccessful surgical procedure [outside of tracheostomy] for treatment ofOSA), changes in facial appearance in addition to cost, complexity, andinconvenience have prevented this procedure from gaining wideacceptance.

Tracheostomy is typically the most effective and definitive surgicaltherapy for OSA. The oropharynx obstructed in OSA is simply bypassed bycreating a hole in the trachea and inserting a tube to maintain a patentairway. This therapy has become less common due to the success of CPAP,and significant social stigma prevents the widespread use of thistechnique for most patients.

Radiofrequency (Somnoplasty) induces thermal lesions in the palate (forprimary snoring) or tongue-base (for patients with OSA) whichsubsequently scar and resorb. This technique has not proved effectivefor OSA, as the majority of patients exhibit narrowing below the levelat which the lesion is placed, and a relapse of snoring is typicallyseen 1-2 years following soft palate application in patients withprimary snoring.

Injection Snoreplasty and scar-tissue inducing implants, likeradiofrequency, induce scarring of the soft palate. While some temporarybenefit is seen in patients with primary snoring and milder forms ofapnea, recurrence of symptoms is often seen, and little (if any)long-term data is currently available.

Tongue-Suture techniques (Repose) utilize a nonresorbable suspensionsuture to advance the hyoid or tongue base; little (if any) long-termdata related to this technique is currently available.

Clinicians, however, often offer a “shotgun” approach to all-cornerswith OSA (i.e., oral appliances are fabricated for all-corners), and nospecific technique or mechanism is utilized in order to predict a givenindividual's probability of response to therapy (prior to appliancefabrication and initiation of treatment). As an alternative, cliniciansoften rely upon resolution of symptoms (after titration has beenperformed) as a means to judge response to therapy, but this isperformed only after the appliance has been fabricated and treatmentinitiated. Unfortunately, beyond the generalized guidelines listedabove, clinicians are currently unable to predict in advance whichindividuals will uniquely respond to OAT treatment and, therefore, whoare the most appropriate candidates for this form of OSA therapy.

Similarly, surgeons involved in performing mandibular advancement (ortongue-base) surgery in patients with OSA currently have no means ofpredicting how far the mandible (or tongue base) must be advanced in anygiven individual in order to affect a cure of upper airway obstruction.This inability to predict response to therapy often leads toinappropriate appliance fabrication and/or inappropriate or inadequatesurgical advancement in patients who will not, by reasons of anatomicalexpansion or physiologic improvement, respond to therapy.

While mandibular protrusion/advancement is the basic mechanismimplemented by OAT, it is generally accepted that oral appliances workby affecting both anatomic expansion of the tongue-base region andphysiologic reduction of soft tissue compliance (of the upper airway)during sleep. While obstruction is accepted to be a dynamic (ornon-fixed) process, anatomic expansion in this case (per Poiseuille'sLaw) refers to the ability to expand the most critical (or stenotic)site of proximal narrowing of the upper airway (MCSPN) above the glotticopening. Per Poiseuille's law, small changes in the radius of the tubeat its narrowest point affect exponential changes in airflow (the radiusin this equation is raised to the fourth power). For example (all elsebeing equal) according to Poiseuille's law, doubling the radius of thetube at its narrowest point increases airflow by a factor of sixteen.

It would therefore be advantageous to provide a system and method ofproviding objective data to predict the efficacy of tongue-basetherapies, such as various nonsurgical and surgical tongue-basetherapies, the response to both OAT treatment, and mandibularadvancement surgery in patients with OSA. Moreover, it would beadvantageous to provide a system and method for generating suchpredictions in a user-friendly and reliable manner.

BRIEF SUMMARY OF THE INVENTION

The present invention addresses the above needs and achieves otheradvantages by providing a system, method, and computer-readable mediumfor predicting the efficacy of tongue-base therapies. Embodiments of thepresent invention provide the capability to utilize airway measurementsas obtained from a variety of awake or asleep upper airway measurementtechniques to determine a probability of a response to a tongue-basetreatment, such as the response to OAT and mandibular advancementsurgery in patients with OSA. As such, embodiments of the presentinvention provide the probability of a patient's response to varioustongue-base treatments based on objective data.

According to one embodiment of the present invention, a method forpredicting a response to tongue-base therapies is provided. The methodincludes generating a plurality of images of at least a portion of apatient's anatomy (during either wakefulness or sleep states), acquiringdata indicative of the portion of the patient's anatomy from the images,and determining a probability of a response of the patient to atongue-base treatment based on the acquired data. For example, themethod could determine the probability of a response to treatment forobstructive sleep apnea, such as OAT treatment, tongue-base directedtherapies, and mandibular advancement surgery. In an additionalembodiment, a computer-readable medium containing instructions may beconstructed for causing a processing element to perform the methoddescribed herein.

Various aspects of the method include generating supine hypotonic imagesof an upper airway of the patient with the patient's head and neck in aneutral standard position. In addition, the generating step may includegenerating at least one image of an airway with the mandible at rest andthe mandible at an advanced position, while the acquiring step mayinclude acquiring an image of an anterior/posterior measurement and/or alateral measurement of a most critical site of proximal narrowing of theupper airway (MCSPN) with the mandible at rest and the mandible at theadvanced position. The acquiring step could further include acquiring anarea of a MCSPN of the airway at rest and the mandible maximallyadvanced, as well as acquiring a percentage area airway expansion(PAAE).

Moreover, additional aspects of the method include inputtingpatient-specific data, such as body mass index, respiratory disturbanceindex, apnea hypopnea index, age, neck circumference, and/or gender. Themethod could also include displaying the probability of a response as agraphical image. The method may further include capturing dataindicative of at least a portion of a patient's anatomy, andsubsequently generating the at least one image based on the captureddata.

A further embodiment of the present invention provides a system forpredicting a response to tongue-base therapies. In particular, thesystem includes a device (e.g., an endoscope, acoustic pharyngometer,ultrasound, MRI, or CT scanner) for capturing data indicative of atleast a portion of a patient's anatomy, and a processing element. Theprocessing element is in communication with the device and is configuredfor generating images based on the captured data, acquiring dataindicative of the portion of the patient's anatomy from the images, anddetermining a probability of a response of the patient to a tongue-basetreatment based on the acquired data. According to one aspect of thesystem, the processing element comprises a graphical user interface fordisplaying the image(s). The graphical user interface may also becapable of displaying an image representative of the probability of aresponse.

The present invention has many advantages. For example, the presentinvention provides a cost effective technique for determining theprobability of response to various tongue-base therapies. In addition,methods of the present invention may be performed efficiently, are non-or minimally invasive, and practical (easily utilized in an averageclinician's private office). Embodiments of the present invention allowdirect measurement of the upper airway during the awake or supine REMsleep state, are easy and comfortable for the patient, and reliable. Thepresent invention also enables rapid measurement of MCSPN volume duringboth supine (maximally protruded mandibular position) and hypotonicsupine (mandible at rest) positions of the mandible, as well as rapidcalculation of probability of the success/failure at a defined RDIlevel. Furthermore, once individual patient-specific variables (RDI,BMI, age, and/or gender) are entered into the processing element by theclinician, and objective airway measurements performed, calculation ofthe probability of treatment success is then performed by the processingelement, and the clinician and patient will then be able to proceedbased upon objective information.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

Having thus described the invention in general terms, reference will nowbe made to the accompanying drawings, which are not necessarily drawn toscale, and wherein:

FIG. 1 depicts a system for predicting the response to tongue-basetherapies;

FIGS. 2A-2D illustrate endoscopic views of the upper airway of apatient;

FIGS. 3A-3B illustrate endoscopic views of the upper airway of apatient;

FIG. 4 is a flowchart of an exemplary method for predicting a responseto tongue-base therapies;

FIG. 5 is a graph illustrating the expected relationship between bodymass index and percentage volumetric airway expansion;

FIG. 6 is a graph illustrating the expected relationship betweenrespiratory disturbance index and percentage volumetric airwayexpansion;

FIG. 7 is a graph illustrating the expected relationship betweenrespiratory disturbance index, body mass index, and percentagevolumetric airway expansion;

FIG. 8 is a perspective view of a probability box; and

FIG. 9 is a perspective view of the expected relationship betweenrespiratory disturbance index, body mass index, and percentagevolumetric airway expansion plotted within a probability box.

DETAILED DESCRIPTION OF THE INVENTION

The present invention now will be described more fully hereinafter withreference to the accompanying drawings, in which some, but not allembodiments of the invention are shown. Indeed, the invention may beembodied in many different forms and should not be construed as limitedto the embodiments set forth herein; rather, these embodiments areprovided so that this disclosure will satisfy applicable legalrequirements. Like numbers refer to like elements throughout.

Until recently, the American Academy of Sleep Medicine has utilizedseverity of disease to suggest those groups of patients who may respondbest to therapy with oral appliances, but these guidelines serve asgeneral predictors only, as a given individual's unique response totreatment (even in mild-moderate cases) is currently unpredictable. Forinstance, many patients with mild-moderate OSA who attempt treatmentwith OAT may fail to obtain a therapeutic reduction of the ApneaHypopnea Index (AHI) or Respiratory Disturbance Index (RDI) even afterfull appliance titration.

When the MCSPN shows adequate expansion with forward posturing (oradvancement) of the mandible, a favorable response to OAT therapy isoften seen (i.e., when a critical area (CAAE) or volume of airwayexpansion (CVAE) or more specifically, a critical percentage of airwayvolumetric expansion (PVAE) at MCSPN is achieved, effectiveness of OATis improved). Unfortunately, clinicians do not currently have apractical means to evaluate MCSPN or PVAE during mandibular protrusion(either in the awake, or sleep state) and, therefore, the ability topredict who will respond therapeutically to OA therapy is problematic.PVAE (enough to attain CVAE) will vary, based upon the presentingbaseline hypotonic MCSPN size, body mass index (BMI), age, gender, neckcircumference, and presenting RDI.

Further complicating this problem is that there is not a direct linearrelationship (even in patients with mild-moderate OSA severities)between degree of mandibular protrusion and degree of expansion of theupper airway at MCSPN (i.e., in some individuals who are able toprotrude the mandible only a small amount, a large degree (orpercentage) of expansion may occur. However, the opposite is also true:some patients who protrude the mandible quite far may exhibit minimal orno degree of airway expansion.

Based upon polysomnographic calculation of the AHI, it is accepted thatthe more elevated the AHI, the more diffuse soft tissue collapse occurs(i.e., higher soft tissue compliance (STC) is seen in patients with moresevere OSA, while lower STC is seen in milder forms of OSA). Thisanatomic region of airway narrowing is not able to be easily accessed,identified, or measured during routine intra-oral or extra-oral clinicalexam. Awake lateral cephalometry (utilizing a barium-swallow techniqueat end-expiration) may allow assessment of the pattern of airwaynarrowing, but is taken in the upright position and is not widely used.Awake acoustic pharyngometry has been suggested as a means of evaluatingSTC, airway measurements, and airway expansion; however, practical useof this technology has proven difficult as technical difficultiesacquiring a consistent waveform are often encountered, precise anatomicrelations cannot be identified, measurements are obtained duringwakefulness, and interpretation of generated clinical data is oftenambiguous (no predictive capability is attained with this device).

Critical closing pressure (Pcrit) is also higher in OSA patients thannormal patients (less negative pressure is required to affect airwayclosure in OSA patients than in normal patients). Calculation of Pcritis confined to specialized institutional research facilities, and simpleanatomic localization of airway narrowing can prove problematic.

Awake supine and/or upright endoscopic evaluation of the upper airway(utilizing a hypotonic technique, and with the airway size evaluatedboth with the mandible at rest and maximally advanced) has beenperformed for many years; without a means to objectively measureendoscopic changes in upper airway volume, however, the resultingsubjective exam is prone to examiner bias and is not considered reliable(and once again, is typically performed during wakefulness).Anesthetically-sedated (and nocturnal endoscopy) has also been reported,but this is not commonly performed (certainly not under the conditionsof monitored polysomnography) and suffers from the same subjective bias.Intra- and inter-examiner reliability (based upon published kappavalues) is low with this subjective technique.

A PVAE (to CVAE), as defined by resolution of the AHI (thereby loweringPcrit and STC) in relation to mandibular advancement and the MCSPN isneeded in patients with OSA to eliminate upper airway obstruction. ThisPVAE may or may not be reached for any given individual via mandibularprotrusion, as MCSPN expansion is not necessarily linearly related tothe amount of mandibular protrusion (the actual amount, or distance, ofmaximal mandibular protrusion varies between patients, and the amount ofmandibular protrusive range of motion is only important in relation tothe OA titration). It is generally assumed, however, that the lower thepresenting RDI and BMI, the more linear this relationship betweenmandibular advancement and AHI becomes.

Airway size (for a given individual) is also a factor of genetics andenvironmental influences, and the degree of MCSPN expansion (or PVAE)during mandibular protrusion may be affected by age, gender, and theability of the patient to protrude the mandible.

Airway size may actually diminish with age and weight gain, as theassociated soft tissues become more compliant, and centrally-drivenmuscular dilation is unable to compensate for the added soft tissueload/burden. Increased BMI is also often associated with smaller andmore collapsible airways, as added adipose burden on the upper airwaydilator muscles prevents adequate dilation and maintenance of MCSPNduring the sleep state (particularly during supine REM sleep). Bydefinition, increased AHI is related to increased susceptibility toobstruction. Finally, males (it is felt) are generally more susceptibleto obstruction than females (although this is not always so), possiblyreflecting a protective hormonal effect (at least until menopause) infemales.

As opposed to guidelines focusing on generalized groupings of largenumbers of patients, new technologies and techniques which permitcalculation of PVAE of the upper airway at MCSPN (initially [for OAtherapy] from mandibular retruded (hypotonic) to maximally (tolerable)protruded (or advanced), but also comparing any pretreatment topostreatment tongue base expansion method or technique), whileadditionally accounting for variables of RDI and BMI, age, and genderwill allow calculation of probability of response to tongue-basetherapies in individual patients with OSA. The most immediateapplication of this idea is to predict probability of response totherapy with oral appliance therapy.

A tool which allows measurement of MCSPN and PVAE in relation tomandibular protrusion during the wake state, but which also factors thedifference in percentage of airway closure during sleep and variablesnoted above, would be of benefit in predicting response to therapy inindividual patients (i.e., probability of response) over the range of anindividual's range of mandibular protrusion, and thereby lead to moreefficient and appropriate application of OA and surgical mandibularadvancement therapy to the OSA population (thus, more efficient andpractical use of health-care financial resources).

While evaluation of MCSPN and PVAE during supine wakefulness may allow amore straightforward exam process (and avoids the technical difficultyof evaluation during sleep state), complicating this calculation is thefact that for MCSPN sleep state volumetric size often differs from thatseen during wakefulness. This diminution in airway size during supineREM sleep (the most vulnerable body position and stage of sleep) shouldbe accounted for in any therapeutic or predictive process.

Positional influences of supine versus non-supine sleep also add furthercomplexity, as supine sleep is recognized to be the most vulnerableposition for airway obstruction. Prior studies have shown thatpharyngeal length can be altered by longitudinal tension. An elongatedpharynx (as produced through cervical extension) based on tractionforces has been shown to have less collapsibility than a shorter (morecompliant) airway. Pharyngeal length as defined in the seated position(as often is utilized with the acoustic pharyngometry technique) couldarguably be under different mechanical forces based on gravitational andlong volume tethering effects as compared with the supine position,thereby causing distortion of the measurement. It can be assumed,however, that for any given upright or supine hypotonic MCSPN notedduring the wake state, this same anatomic location/site will be smallerduring supine hypotonic REM sleep, as dilating muscle activity abatesduring this phase of sleep. The degree of cervical flexion/extensionduring required measurements for this device are accounted for andcontrolled as defined below.

Genioglossus muscle tone in the supine position is augmented during theawake state, but lost during sleep (for this reason, acousticpharyngometry is often performed in the upright position, in order tominimize this influence of augmented muscle tone). This effect may benoted endoscopically in some, but not all patients.

Inherent to any discussion regarding treatment success (or probabilitythereof) must take into consideration the definition of success (whichin this case, is the reduction of RDI to 10 or less).

As opposed to subjective evaluation, CT and MRI evaluation of the upperairway has also been performed as a means of measuring upper airwayvolume. While measurements utilizing these (and other) techniques formthe basis for predictions to response to treatment, limitations to thesetechniques relate to inability to assess the airway in the hypotonic(i.e., end-expiration) supine REM sleep state, slow scan times, andfinancial practicality.

New technologies are currently available that allow for objectiveinstantaneous endoscopic measurements. Endoscopy (while one of manytechnologies allowing airway measurements) can be considered as afoundational tool for this technique, as endoscopy is often performed byotolaryngologists, oral & maxillofacial surgeons, and pulmonologistsand, hence, widely available (general dentists who offer treatment forOSA may also begin offering this service). These new technologies forobjective endoscopic measurements, however, have not been widely appliedto the medical arena, as most uses have been in various industrialsettings (i.e., aerospace and utility industries).

Utilizing a combination of stereo measurements (to allow measurementsfrom non-perpendicular orientations) and simple geometric triangulationmethods, the distance between two points, total length, and areameasurements can now be objectively calculated at MCSPN while themandible is at rest, and compared to the same measurements while the jawis maximally advanced (in order to derive a PVAE measurement).

Generally, the present invention provides methods for predicting theefficacy of tongue-base therapies, such as (but not limited to) theresponse to both OAT treatment, surgical and non-surgical tongue-basetherapies, and mandibular advancement surgery in patients with OSA. Inparticular, the present invention includes generating images of theupper airway, acquiring data from the images, and using this data inconjunction with an algorithm to generate the probability of response toa particular treatment for a patient, such as treatment to OSA.

As will be explained in further detail below, once an individualpatient's data for percentage of airway expansion is determined (by oneof various measurement technologies), patient specific data is alsoinput (such as BMI, RDI, neck circumference, age, and/or gender), and aprocessing element and associated software then computes thepatient-derived data in relation to a probability curve (generated as aresult of study of a large reference population of patients). Where theindividual patient's data falls in relation to the curve then determinesan individual patient's probability of response to a particulartongue-base therapy. Moreover, derivation of the critical airwayexpansion (according to a given patient's BMI, age, gender, and/or RDI)can also allow calculation of how much forward movement of themandible/jaw/tongue base is needed in any given individual for ananticipated surgical procedure. As such, methods of the presentinvention allow clinicians to objectively and more reliably predictwhich patients are candidates for OSA treatment.

Although reference is made herein to predicting the response to OSAtreatment, it is understood that the present invention is capable ofpredicting the response to various tongue-base therapies. In thisregard, the present invention may be employed to predict other responsesto treatments, as well as for diagnostic purposes. For instance, thepresent invention could be used for predicting the response to surgicaltherapy, response to hyoid suspension techniques, tongue-base suturesuspension techniques, radiofrequency techniques, genioglossusadvancement, and mandibular advancement techniques.

One embodiment provides a system 10 for carrying out methods of thepresent invention. FIG. 1 illustrates a device 12 that is incommunication with a processing element 14. The device 12 could bedirectly connected to the processing element 14 or remotely communicatetherewith, such as via wireless or network communications. The device 12preferably communicates captured data to the processing element in realtime, although batch processing could be implemented if desired.

More specifically, the device 12 captures images indicative of portionsof the anatomy, such as the upper airway shown in FIG. 2. For example,endoscopes, CT or MRI scans, acoustic devices, or ultrasound techniquescould be employed to capture an image or acquire a measurement of theupper airway with the head in a neutral supine reference position. Morespecifically, small diameter scopes (e.g., 4 mm or less) are currentlyused for upper airway endoscopic evaluation. These endoscopic devicescould utilize stereoscopic lenses (of adequate focal lengths to insureaccuracy of measurements) in order to capture images for readilyacquiring measurements from images in multiple directions. According toone embodiment of the present invention, the device could be similar toan IPLEX® endoscope manufactured by Olympus Optical Co., Ltd.

The processing element 14 may include any number of conventionalhardware and software components, as depicted in FIG. 1. For example,the processing element could include memory (e.g., RAM), mass storage(e.g., magnetic hard disk or optical storage disk), I/O controller,network interface (e.g., Internet, intranet, or extranet), bus fortransferring data or power between processing element components orbetween processing elements, and/or graphical interface. The graphicalinterface, as known to those of skill in the art, provide methods fordisplaying and interacting with images generated in response to datacaptured by the device 12 onto a monitor or similar viewing device.

In addition, the processing element includes a processor that couldinclude one or more applications (e.g., programs) and a standardoperating system. The processing element 14 is preferably a computer,such as a personal computer or workstation, although the processingelement could be any device capable of performing methods of the presentinvention. For instance, the processing element 14 could be a portabledevice, such as a laptop, a personal data assistant, or mobile phone.Furthermore, the device 12 could be in communication with one or moreprocessing elements 14, and the processing element is capable ofcommunicating with other processing elements residing in a network.

As mentioned above, the processing element 14 is capable of displayingimages in real time such that a video of the captured data may be shown,or still photographs may be taken at any time in order to acquire datadirectly from the graphical interface or from a printout of the image.However, it is also understood that the device 12 could collect data atpre-determined times, rather than sending real-time data to theprocessing element 14, and send the data to the processing element fordisplay by the graphical interface or for output by an output device,such as a printer. Therefore, although a graphical interface ispreferred, it is possible to incorporate the processing element 14without a display and to instead provide a printout of the image(s), orto utilize any other technique for viewing images of the captured dataand acquiring data from the images. The processing element 14 is capableof maintaining a permanent record of the captured data and images forfuture use or record keeping, which allows a user to store and editpreviously created images.

FIGS. 2A-2D and 3A-3B illustrate images of the upper airway captured bythe device 12 and generated by the processing element 14, which are usedto acquire various measurements according to one embodiment of thepresent invention. Thus, the processing element 14 is capable of using agraphical user interface to acquire various measurements on thedisplayed image (e.g., distance, area, and volume). In this regard, FIG.2A illustrates an image of a hypotonic supine upper airway endoscopicview (mandible at rest/retruded position) taken during either supine REMsleep or during the supine awake state (with the head/neck in a neutralstandard reference position), where A1 corresponds to ananterior-posterior measurement of the MCSPN (from posterior pharyngealwall to epiglottis tip), and B1 corresponds to a lateral measurement ofthe MCSPN (widest aperture in lateral dimension). FIG. 2B depicts animage of a supine upper airway endoscopic view with the mandiblemaximally advanced, where A2 corresponds to the MCSPN with the mandibleat a maximally advanced position, and B2 corresponds to the lateralairway with the mandible at a maximally advanced position. Furthermore,FIG. 2C shows an image of the Mueller maneuver, and FIG. 2D illustratesan image of the retropalatal endoscopic view. The anterior-posteriorchange is calculated as:(A2−A1/A1×100)−PAAC=PAAE _(AP),where PAAC is percentage of area airway collapse and PAAE is thepercentage of area airway expansion, and the lateral change iscalculated as:(B2−B1/B1×100)−PAAC=PAAE _(lateral).

For clinical utility, any calculation of PAAE should account for thepercentage of area decrease of the critical airway size that occursnaturally during sleep (i.e., PAAC), or the percentage of area airwaycollapse during sleep (i.e., percentage airway collapse that occurs intransition from wake to REM sleep). FIGS. 3A-B show that area changescan be calculated for the supine hypotonic upper airway endoscopic viewwith the mandible at rest (FIG. 3A), and for the supine upper airwayendoscopic view with the mandible maximally advanced (FIG. 3B).Similarly, the area change for any given segment of the upper airway maybe calculated using the following equation:(C2−C1/C1×100)−PAAC=PAAE.

It is understood that the general focus is on expansion of the narrowestportion of the tongue base (i.e., MCSPN), which is determined initiallyas an increase in area (i.e., linear measurements). In some patients,volumetric changes over a given segment of the airway will be required,therefore, incorporating a third dimensional factor. Therefore, linear,area, and volumetric measurements (e.g., PVAC and PVAE) may be readilymade using the images generated by the processing element 14, and thatdata indicative of the upper airway may be acquired using the images.

PAAC (and PVAC) are constants that can be determined based uponobjective airway measurements of a large group of reference patientsduring hypotonic supine awake and hypotonic supine REM sleep studies(again, using standard neutral reference head positions). Calculation ofthe PAAC (or PVAC) during the generation of the reference database willfacilitate the creation of a constant, which (when factored intomeasurements made in any individual) will allow subsequent assessment inindividual patients during the awake state. The reference database willalso be assessed for treatment success to oral appliance therapy (i.e.,tongue-base expansion).

The MCSPN of proximal upper airway narrowing during hypotonic supine REMsleep can be defined as the narrowest proximal (hypopharyngeal) portionof the airway (i.e., closest to, but above the glottis); the assumptionis that for most (but not all) patients, the retroepiglottic airwaysegment is typically the MCSPN. In addition, the ability of the MCSPN toexpand with any therapeutic maneuver (for example, maximal forwardposturing of the mandible in patients with oral appliances) (defined asPVAE), during hypotonic supine REM sleep, as well as supine hypotonicawake state, and the variation in AHI or RDI resulting (during sleep)from these tested positions (in a large reference group of patients withsleep-related breathing disorders and OSA) can be defined.Sub-categorization of these groups based upon BMI, age, gender, and RDIcan be implemented, and thereby permit calculation of a series of linearand nonlinear mathematical relationship curves (for example, therelationship of PAAE to BMI, age, gender, and/or RDI). Measuring themaximal comfortable forward position of the mandible and the resultingPAAE, when correlated to resulting BMI, age, gender, and presenting AHIor RDI allows the calculation of a CAAE. Furthermore, the percentagedecrease in MCSPN volume (or size) from upright hypotonic wake tohypotonic supine REM sleep (based upon AHI or RDI spectrum from mild tosevere) in a large reference group of patients with sleep-relatedbreathing disorders can be defined in a similar manner. Thesemeasurements allow for creation of a series of mathematicalrelationships to compare sleep and wake states, and can be expressed asconstants for a given presenting AHI, RDI, gender, age, and/or BMI. Assuch, each of these measurements and calculations can be derived from astudy of a large reference population of patients and entered into adatabase. The resulting reference database can serve as the basis forthe probability boxes, which are explained in further detail below.

Additionally, embodiments of the present invention can employ amultivariate algorithm to calculate the statistical probability oftreatment success over a given range of airway expansion (from MCSPNairway volume measured at both mandibular retruded and maximally, i.e.,comfortably, protruded) to a given PAAE, (while accounting for AHI, RDI,age, gender, and/or BMI based on the data acquired from the images, aswell as the various parameters discussed above. Thus, the probability oftreatment success for any individual will be based upon a comparison ofpatient-specific measurements to the reference database discussed above.In general, FIG. 4 illustrates that a method according to one embodimentof the present invention includes generating a plurality of images of aportion of a patient's anatomy (block 32), acquiring data indicative ofthe patient's anatomy from the images (block 34), and determining theprobability of a response of the patient to a tongue-base treatmentbased on the acquired data (block 36).

For example, FIGS. 5-9 illustrate various exemplary datasets (andprobability curves) generated by the system 10 of the present invention.In particular, FIG. 5 depicts an expected relationship between BMI andPAAE (similar curves could be generated for PVAE), while FIG. 6 shows anexpected relationship between RDI and PAAE. PAAE is calculated using theabove technique shown and described with respect to FIGS. 2A-2D and3A-3B, as well as the various parameters described above, RDI (orRespiratory Disturbance Index) is known to those or ordinary skill inthe art as the number of hourly apneas+hypopneas+respiratoryeffort-related arousals, and BMI is known to those of ordinary skill inthe art as the measure of body mass based on height and weight of apatient. Thus, FIGS. 5 and 6 demonstrate that the expected relationshipis non-linear, which indicates that the present invention is capable ofcorrelating variables that are generally otherwise incapable of beingreliably used to predict a given individual's response to tongue-basetreatment.

Moreover, FIG. 7 illustrates the expected relationship between RDI, BMI,and PAAE in three coordinates. FIG. 8 depicts a probability box thatincludes low, intermediate, and high probability portions, and FIG. 9shows an expected relationship between RDI, BMI, and PAAE shown inthree-dimensional space within a probability box. Therefore, thosepoints that fall above the curve shown in FIG. 9 would have a highprobability of responding to tongue-base treatment, whereas those pointsthat fall below the curve in FIG. 9 would have a low probability ofresponding to tongue-base treatment. Accordingly, those points that fallclose to the curve would have an intermediate probability of respondingto tongue-base treatment. Thus, given a specific patient's PAAE, BMI,age, gender, and RDI, a series of probability boxes and curves can becreated which allow calculation of the patient's probability of responseto OSA (tongue-base) treatment using FIG. 9. Mathematical calculationand description of the shape of the probability curve is performed basedupon the reference data.

It is understood that cervical (neck) flexion and extension will shiftthe relative position of the curve within the probability box; flexion(compared with the standard neutral reference measurement position) willtend to cause a relative upward shift in the entire curve, therebyincreasing the probability of treatment failure. Cervical (neck)extension (in relation to the standard neutral reference measurement),conversely, will tend to cause a downward shift in the entire curve,thereby increasing the probability of treatment success.

It is understood that several different probability boxes may begenerated in order to better predict different patient's response to OSA(tongue-base) treatment. For instance, the same coordinates of BMI, RDI,and PAAE (defining the three axes of space) can be generated for aseries of male patients of varying ages (or age groups), i.e., ages20-30, 31-40, etc. Each of these curves may have a slight varying shapedepending upon characteristics for this group of patients. Similarly,the same coordinates can be used to generate a series of probabilitycurves for female patients of varying age groups, i.e., age 20-30, age31-40, etc. Once again, each of these curves may have a slight varyingshape so as to accurately reflect subtle differences in each grouping ofthese patients. As an alternative to RDI, AHI could be plotted alongwith BMI and PAAE in order to generate an additional or alternativecurve within the probability box. It is also understood that the system10 of the present invention is not limited to generating probabilityboxes and curves therein for predicting a response to tongue-basetreatment. For example, the processing element 14 could generate andoutput a value (e.g., 90%), such as on the graphical user interface orwith an output device, that corresponds to the probability of apatient's response to an OSA treatment.

According to one aspect of the present invention, the system 10generally operates under control of a computer program product. Thecomputer program product for performing the methods of embodiments ofthe present invention includes a computer-readable storage medium, suchas the memory device associated with a processing element, andcomputer-readable program code portions, such as a series of computerinstructions, embodied in the computer-readable storage medium.

In this regard, FIG. 4 is a control flow diagram of a method and programproduct according to the invention. It will be understood that eachblock or step of the control flow diagram, and combinations of blocks inthe control flow diagram, can be implemented by computer programinstructions. These computer program instructions may be loaded onto aprocessing element, such as a computer, server, or other programmableapparatus, to produce a machine, such that the instructions whichexecute on the processing element create means for implementing thefunctions specified in the block(s) or step(s) of the control flowdiagrams. These computer program instructions may also be stored in acomputer-readable memory that can direct the processing element tofunction in a particular manner, such that the instructions stored inthe computer-readable memory produce an article of manufacture includinginstruction means which implement the function specified in the block(s)or step(s) of the control flow diagram. The computer programinstructions may also be loaded onto the processing element to cause aseries of operational steps to be performed on the processing element toproduce a computer implemented process such that the instructions whichexecute on the processing element provide steps for implementing thefunctions specified in the block(s) or step(s) of the control flowdiagram.

Accordingly, blocks or steps of the control flow diagram supportcombinations of means for performing the specified functions,combinations of steps for performing the specified functions, andprogram instruction means for performing the specified functions. Itwill also be understood that each block or step of the control flowdiagram, and combinations of blocks or steps in the control flowdiagram, can be implemented by special purpose hardware-based computersystems which perform the specified functions or steps, or combinationsof special purpose hardware and computer instructions.

The present invention has many advantages. For example, the presentinvention provides a cost effective technique for determining theprobability of response to various tongue-base therapies (particularlyas it relates to treatment of obstructive sleep apnea). In addition,embodiments of the present invention may be performed efficiently, arenon-minimally invasive, and practical (easily utilized in an averageclinician's private office). Embodiments of the present invention allowdirect measurement of the upper airway during the wake state, are easyand comfortable for the patient, as well as reliable. The presentinvention also enables rapid measurement of MCSPN volume during bothawake supine (maximally protruded mandibular position) and awakehypotonic supine (mandible at rest) positions of the mandible, as wellas rapid calculation of probability of the success/failure at a definedRDI level. Furthermore, once individual patient-specific variables (RDI,BMI, age, and/or gender) are entered into the processing element by theclinician, and objective airway measurements performed, calculation ofthe probability of treatment success is then performed by the processingelement, and the clinician and patient will then be able to proceedbased upon objective information.

Many modifications and other embodiments of the invention set forthherein will come to mind to one skilled in the art to which thisinvention pertains having the benefit of the teachings presented in theforegoing descriptions and the associated drawings. Therefore, it is tobe understood that the invention is not to be limited to the specificembodiments disclosed and that modifications and other embodiments areintended to be included within the scope of the appended claims.Although specific terms are employed herein, they are used in a genericand descriptive sense only and not for purposes of limitation.

1. A storage method in the form of a memory device for predicting aresponse to tongue-base therapies comprising: generating a plurality ofimages of an axial view of a patient's upper airway, wherein each imagedepicts a cross-sectional plane of the patient's upper airway, thecross-sectional plane extending substantially transverse to alongitudinal axis of the patient's pharynx; acquiring data indicative ofthe patient's upper airway from the images, wherein the data comprisesat least an anterior/posterior measurement and a lateral measurementboth determined from the images of the axial view of the patient's upperairway; and determining a probability of a patient's response to atongue-base treatment based on the acquired data and patient-specificphysiological data, wherein the probability is determined by comparingthe acquired data and the patient-specific physiological data for thepatient to an expected relationship between similar acquired data andpatient-specific physiological data.
 2. The method according to claim 1,wherein the patient-specific physiological data comprises at least oneof body mass index, respiratory disturbance index or apnea hypopneaindex, age, neck circumference, or gender.
 3. The method according toclaim 1, wherein generating comprises generating a plurality of imagesduring a wakefulness state or a sleep state.
 4. The method according toclaim 1, wherein acquiring comprises acquiring a third measurement ofthe upper airway such that the anterior/posterior measurement, lateralmeasurement, and the third measurement provide information regarding avolumetric change of the patient's upper airway.
 5. The method of claim1, wherein determining comprises calculating a statistical probabilityof a patient's response to a tongue-base treatment using a multivariatealgorithm.
 6. The method of claim 1, wherein generating comprisesgenerating a plurality of images of an axial view of a patient's upperairway in a retroepiglottic region, and wherein acquiring comprisesacquiring an anterior/posterior measurement and a lateral measurementboth taken from the axial view of the patient's upper airway in theretroepiglottic region.
 7. The method of claim 1, further comprisingdetermining an expected relationship between similar acquired data andpatient-specific physiological data obtained from a plurality ofpatients.
 8. The method according to claim I, further comprisingdisplaying the expected relationship as a graphical image, whereindetermining the probability comprises determining a location of theacquired data and the patient-specific physiological data for thepatient on the graphical image.
 9. The method of claim 8, whereindisplaying comprises displaying the expected relationship as a graphicalimage in three-dimensional space.
 10. The method according to claim 1,wherein determining comprises determining the probability of a responseto treatment for obstructive sleep apnea.
 11. The method according toclaim 10, wherein determining comprises determining the probability ofresponse to at least one of a treatment of obstructive sleep apnea withoral appliances, tongue-base directed therapies, or mandibularadvancement surgery.
 12. The method according to claim 1, furthercomprising capturing data indicative of at least a portion of apatient's upper airway.
 13. The method according to claim 12, whereingenerating comprises generating the at least one image based on thecaptured data.
 14. The method of claim 1, wherein the anterior/posteriormeasurement comprises a measurement between the patient's posteriorpharyngeal wall and epiglottis tip.
 15. The method of claim 14, whereinthe lateral measurement comprises a lateral measurement between thepharyngeal wall that is substantially transverse to theanterior-posterior measurement.
 16. The method according to claim 1,wherein generating comprises generating at least one supine hypotonicimage of an upper airway of the patient with the patient's head and neckin a neutral standard position.
 17. The method according to claim 16,wherein generating comprises generating at least one image of an airwaywith the mandible at rest and the mandible at an advanced position. 18.The method according to claim 17, wherein acquiring comprises acquiringan anterior/posterior measurement and a lateral measurement of a mostcritical site of proximal narrowing of the upper airway with themandible at rest and the mandible at an advanced position.
 19. Themethod according to claim 17, wherein acquiring comprises acquiring atleast one of an area of a most critical site of proximal narrowing ofthe upper airway with the mandible at rest or the mandible at anadvanced position.
 20. The method according to claim 19, whereinacquiring comprises acquiring a percentage area airway expansion.
 21. Acomputer-readable medium containing instructions for causing aprocessing element to perform the steps of: generating a plurality ofimages of an axial view of a patient's upper airway, wherein each imagedepicts a cross-sectional plane of the patient's upper airway, thecross-sectional plane extending substantially transverse to alongitudinal axis of the patient's pharynx; acquiring data indicative ofthe patient's upper airway from the images, wherein the data comprisesat least an anterior/posterior measurement and a lateral measurementboth determined from the images of the axial view of the patient's upperairway; and determining a probability of a patient's response to atongue-base treatment based on the acquired data and patient-specificphysiological data, wherein the probability is determined by comparingthe acquired data and the patient-specific physiological data for thepatient to an expected relationship between similar acquired data andpatient-specific physiological data.
 22. The computer-readable mediumaccording to claim 21, wherein the patient-specific physiological datacomprises at least one of body mass index, respiratory disturbance indexor apnea hypopnea index, age, neck circumference, or gender.
 23. Thecomputer-readable medium according to claim 21, further comprisingdisplaying the expected relationship as a graphical images, whereindetermining the probability comprises determining a location of theacquired data and the patient-specific physiological data for thepatient on the graphical image.
 24. The computer-readable medium ofclaim 21, further comprising determining an expected relationshipbetween similar acquired data and patient-specific physiological dataobtained from a plurality of patients.
 25. The computer-readable mediumaccording to claim 21, wherein determining comprises determining theprobability of a response to treatment for obstructive sleep apnea. 26.The computer-readable medium according to claim 25, wherein determiningcomprises determining the probability of response to at least one of atreatment of obstructive sleep apnea with oral appliances, tongue-basedirected therapies, or mandibular advancement surgery.
 27. Thecomputer-readable medium according to claim 21, further comprisingcapturing data indicative of at least a portion of a patient's upperairway.
 28. The computer-readable medium according to claim 27, whereingenerating comprises generating the at least one image based on thecaptured data.
 29. The computer-readable medium according to claim 21,wherein generating comprises generating at least one supine hypotonicimage of an upper airway of the patient with the patient's head and neckin a neutral standard position.
 30. The computer-readable mediumaccording to claim 29, wherein generating comprises generating at leastone image of an airway with the mandible at rest and the mandible at anadvanced position.
 31. The computer-readable medium according to claim30, wherein acquiring comprises acquiring an anterior/posteriormeasurement and a lateral measurement of a most critical site ofproximal narrowing of the upper airway with the mandible at rest and themandible at an advanced position.
 32. The computer-readable mediumaccording to claim 30, wherein acquiring comprises acquiring at leastone of an area of a most critical site of proximal narrowing of theupper airway with the mandible at rest or the mandible at an advancedposition.
 33. The computer-readable medium according to claim 32,wherein acquiring comprises acquiring a percentage area airwayexpansion.
 34. A system for predicting a response to tongue-basetherapies comprising: a device for capturing data indicative of an axialview of a patient's upper airway; and a processing element incommunication with the device and for generating a plurality of imagesbased on the captured data, wherein each image depicts a cross-sectionalplane of the patient's upper airway, the cross-sectional plane extendingsubstantially transverse to a longitudinal axis of the patient'spharynx, acquiring data indicative of the patient's upper airway fromthe images, wherein the data comprises at least an anterior/posteriormeasurement and a lateral measurement both determined from the images ofthe axial view of the patient's upper airway, and determining aprobability of a patient's response to a tongue-base treatment based onthe acquired data and patient-specific physiological data, wherein theprobability is determined by comparing the acquired data and thepatient-specific physiological data for the patient to an expectedrelationship between similar acquired data and patient-specificphysiological data.
 35. The system of claim 34, wherein the processingelement is configured to determine an expected relationship betweensimilar acquired data and patient-specific physiological data obtainedfrom a plurality of patients.
 36. The system according to claim 34,wherein the device comprises one of an endoscope, acousticpharyngometer, ultrasound, MRI, or CT scanner.
 37. The system accordingto claim 36, wherein the processing element comprises a graphical userinterface for displaying the plurality of images.
 38. The systemaccording to claim 37, wherein the graphical user interface is capableof displaying an image representative of the expected relationship,wherein the processing element is configured to determine theprobability by locating the acquired data and the patient-specificphysiological data for the patient on the image.
 39. A method forpredicting a response to tongue-base therapies comprising: generating aplurality of images of an axial view of a patient's upper airway in aretroepiglottic region, wherein each image depicts a cross-sectionalplane of the patient's upper airway, the cross-sectional plane extendingsubstantially transverse to a longitudinal axis of the patient'spharynx; acquiring data indicative of the patient's upper airway fromthe images, wherein the data comprises at least an anterior/posteriormeasurement and a lateral measurement both determined from the images ofthe axial view of the patient's upper airway in the retroepiglotticregion; determining an expected relationship between similar acquireddata and patient-specific physiological data obtained from a pluralityof patients; and determining a probability of a patient's response to atongue-base treatment based on a comparison of the acquired data andpatient-specific physiological data for the patient to the expectedrelationship.
 40. The method according to claim 39, further comprisingdisplaying the expected relationship as a graphical image, whereindetermining the probability comprises determining a location of theacquired data and the patient-specific physiological data for thepatient on the graphical image.